Back to Search Start Over

Deep Learning-Enhanced Chemiluminescence Vertical Flow Assay for High-Sensitivity Cardiac Troponin I Testing.

Authors :
Han GR
Goncharov A
Eryilmaz M
Ye S
Joung HA
Ghosh R
Ngo E
Tomoeda A
Lee Y
Ngo K
Melton E
Garner OB
Di Carlo D
Ozcan A
Source :
Small (Weinheim an der Bergstrasse, Germany) [Small] 2025 Feb 05, pp. e2411585. Date of Electronic Publication: 2025 Feb 05.
Publication Year :
2025
Publisher :
Ahead of Print

Abstract

Democratizing biomarker testing at the point-of-care requires innovations that match laboratory-grade sensitivity and precision in an accessible format. Here, high-sensitivity detection of cardiac troponin I (cTnI) is demonstrated through innovations in chemiluminescence-based sensing, imaging, and deep learning-driven analysis. This chemiluminescence vertical flow assay (CL-VFA) enables rapid, low-cost, and precise quantification of cTnI, a key cardiac protein for assessing heart muscle damage and myocardial infarction. The CL-VFA integrates a user-friendly chemiluminescent paper-based sensor, a polymerized enzyme-based conjugate, a portable high-performance CL reader, and a neural network-based cTnI concentration inference algorithm. The CL-VFA measures cTnI over a broad dynamic range covering six orders of magnitude and operates with 50 µL of serum per test, delivering results in 25 min. This system achieves a detection limit of 0.16 pg mL <superscript>-1</superscript> with an average coefficient of variation under 15%, surpassing traditional benchtop analyzers in sensitivity by an order of magnitude. In blinded validation, the computational CL-VFA accurately measures cTnI concentrations in patient samples, demonstrating a robust correlation against a clinical-grade FDA-cleared analyzer. These results highlight the potential of CL-VFA as a robust diagnostic tool for accessible, rapid cardiac biomarker testing that meets the needs of diverse healthcare settings, from emergency care to underserved regions.<br /> (© 2025 The Author(s). Small published by Wiley‐VCH GmbH.)

Details

Language :
English
ISSN :
1613-6829
Database :
MEDLINE
Journal :
Small (Weinheim an der Bergstrasse, Germany)
Publication Type :
Academic Journal
Accession number :
39910838
Full Text :
https://doi.org/10.1002/smll.202411585